What's inside the guide 

If you're under pressure to scale AI agents beyond the pilot phase, this guide will help you make the right call.

Compare four deployment models—custom-built agents, off-the-shelf copilots, embedded SaaS features, and platform-led orchestration. See which ones actually scale and which introduce risk.

Get side-by-side comparisons, technical tradeoffs, and decision points that directly impact delivery speed, ownership, and governance. It's the strategic view your architecture team needs to move fast—and avoid costly dead ends.

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How this guide helps

• See where each model works—and where it breaks: Compare four deployment paths across delivery speed, governance, integration complexity, and long-term scalability.

• Avoid common blockers: Learn how teams are navigating vendor lock-in, siloed tools, disconnected workflows, and unclear ownership.

• Make confident architecture decisions: Understand what each model requires—team roles, integration effort, and delivery tradeoffs—and how those choices affect scale.

• Why more teams are moving to orchestration platforms: See how platform-led strategies help teams roll out agents across systems—without rebuilding from scratch every time.